Data Virtualization

So your company has decided to modernize its systems and migrate to the Cloud. Or, maybe, you're in the middle of this modernization and migration process right now. Taking advantage of the dynamic agility and flexibility of the Cloud offerings is certainly something to look forward to. But how do you ensure that your users can access the data that they need from the various Cloud and on-premise data sources - before, during, and after the migrations?The Cloud vendors will tell you that if you move your data to the Cloud, you won't need technologies like data virtualization. Is this true? Is...

Presented at DATAVERSITY Demo Day – Enterprise Data Management ToolsData fabric and data mesh are two concepts frequently mentioned in conversations surrounding enterprise data management. Over the past two decades, enterprises have managed data by oscillating through cycles of centralization and decentralization. Despite the abundance of options, the conundrum remains — businesses want data to be in one place, and easy to find. Collecting all the data into a single location continues to be a challenge. Data fabric and data mesh designs, powered by data virtualization, can help businesses...

The Journey to Data clarity

The data landscape has become more complex with new use cases like IoT, Streaming and Edge analytics. To better manage enterprise data distributed across data lakes, data warehouses, and many other systems residing on-premises and in the cloud, enterprises are turning to various data management technologies like query accelerators, data virtualization, and data fabrics. Each address specific needs of an organization, but which is the right solution to help you meet your business objectives?Join Denodo for a webinar featuring guest speaker, Forrester VP and Principal Analyst, Noel Yuhanna, to...

The data landscape has become more complex with new use cases like IoT, Streaming and Edge analytics. To better manage enterprise data distributed across data lakes, data warehouses, and many other systems residing on-premises and in the cloud, enterprises are turning to various data management technologies like query accelerators, data virtualization, and data fabrics. Each address specific needs of an organization, but which is the right solution to help you meet your business objectives?Join Denodo for a webinar featuring guest speaker, Forrester VP and Principal Analyst, Noel Yuhanna, to...

The data landscape has become more complex with new use cases like IoT, Streaming and Edge analytics. To better manage enterprise data distributed across data lakes, data warehouses, and many other systems residing on-premises and in the cloud, enterprises are turning to various data management technologies like query accelerators, data virtualization, and data fabrics. Each address specific needs of an organization, but which is the right solution to help you meet your business objectives?Join Denodo for a webinar featuring guest speaker, Forrester VP and Principal Analyst, Noel Yuhanna, to...

So your company has decided to modernize its systems and migrate to the Cloud. Or, maybe, you're in the middle of this modernization and migration process right now. Taking advantage of the dynamic agility and flexibility of the Cloud offerings is certainly something to look forward to. But how do you ensure that your users can access the data that they need from the various Cloud and on-premise data sources - before, during, and after the migrations?The Cloud vendors will tell you that if you move your data to the Cloud, you won't need technologies like data virtualization. Is this true? Is...

With the appearance of cloud object storage services like AWS S3 or Azure ADLS, the data lake has seen an upturn in usage as some of the challenges of the original idea were addressed. However, companies across the globe still find it challenging to adopt data lakes into the corporate data ecosystem. While almost infinite in storage, data retrieval from these sources and integration of the data with the corporate ecosystem is still an arduous task for data engineers. This leads to data lakes becoming either a silo or a secondary form of storage instead of feeding business processes and...

Data architecture is more relevant than ever today, because so many user organizations are migrating data to the cloud, modernizing analytics and data warehouses, deploying data lakes and lakehouses, and adopting new practices for data virtualization, sharing, monetization, and marketplaces.These and other data-driven use cases demand massive volumes of data in every structure imaginable, together with a wide range of processing capabilities. A well-designed, cloud-based data architecture provides a home for such highly diverse data and the numerous use cases it enables.This Tactical...

IDC data shows that between 2021 and 2022 there has been a 10% increase in European organizations that are in the more mature stages of their sustainability initiatives; while for 19% of European organizations, over 10% of their IT budget is driven by sustainability-related actions.Data lies at the heart of an ESG framework, yet it remains a major hurdle. For most organizations data is stored in numerous different silos, from mainframes, to mid-range servers, different data warehouses, and of course the cloud. Enterprises have difficulty bringing all of this data together in a coherent way –...